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Home / School of Computational & Physical Sciences / Department of Computational Studies / B.Sc. Data Science
The Data Science programme equips students with strong foundations in statistical, mathematical, and computational analysis. It develops skills in data visualization and storytelling while enabling students to apply data science techniques for analytics, derive meaningful insights, and support effective decision making.
Through integrated certifications with Qlik and Celonis, students master process mining, machine learning pipelines, big data architectures, and predictive analytics. The curriculum fosters computational rigor and critical thinking, preparing graduates to solve high-impact analytics problems across industries.
Develop expertise in data collection, cleaning, statistical analysis, exploratory data analysis, and visualization using Python, Pandas, NumPy, and Power BI/Tableau.
Gain hands-on skills in supervised and unsupervised learning, predictive modelling, deep learning, natural language processing, and AI-driven data solutions.
Learn to manage and process large-scale datasets using SQL, NoSQL, cloud platforms, distributed computing, and big-data technologies, with emphasis on real-world industry applications.
A three-year specialized degree building computational, statistical, and artificial intelligence expertise.
Programme: B.Sc. Data Science
Specialization: Emerging Technologies & Analytics
Duration: 3 Years (6 Semesters)
Study Mode: Full-Time Undergraduate Programme
Core Academic Focus: Statistical & mathematical foundations, Data analysis & visualization, Machine learning, Big data processing, SQL/NoSQL databases, Process mining, and Predictive analytics
Practical Components: Skills Studio, Qlik Data Architect / Business Analyst certifications, Celonis Process Mining, Power BI/Tableau workshops, Datathons, ideathons, and capstone projects
Learning Pathway: Foundation → Domain Specialisation → Skill Development → Industry Exposure → Certification → Capstone/Project → Research & Innovation → Career/Entrepreneurship
Comprehensive semester-wise course distribution covering advanced statistics, data engineering, machine learning, and process analytics.
Review the mandatory academic qualifications and subject prerequisites required for admission.
For admission to the B.Sc. Data Science programme, candidates must satisfy the following academic prerequisites:
Looking for a programme that matches your interests?
Find Programmes by InterestTargeted competencies and practical mastery achieved by graduates throughout their academic journey.
PSO1: Demonstrate knowledge of programming, databases, data analytics, visualisation, storytelling, quantitative methods and techniques.
PSO2: Apply data science pipelines and tools for descriptive, diagnostic, predictive and prescriptive analytics.
PSO3: Develop dashboards to identify patterns and derive insights using data visualization tools.
PSO4: Formulate data-driven solutions based on systematic research.
Key strengths, experiential learning, and strategic career advantages offered by the programme.
In the era of big data, organizations rely on data-driven intelligence to drive strategic decisions, optimize operations, and uncover predictive insights. Data scientists who bridge statistical acumen with computational power are in high demand across every sector.
The B.Sc. in Data Science programme at Kristu Jayanti University equips students with advanced skills in statistical modeling, programming, data mining, predictive analytics, machine learning, and interactive data visualization.
Choosing this programme enables students to:
Blending mathematical rigor with modern computational workflows, the programme prepares graduates to solve real-world problems and lead business intelligence initiatives.